The current-voltage characteristics of the niobium -aluminum oxide -niobium tunnel junctions have been studied systematically and are compared with numerical simulations based on the microscopic theory of the proximity effeCt. The thickness of the base niobium layer is varied from 35 to 500 nm while the thickness of the aluminum layer is kept constant (about 9 nm). In a separate series of experiments the aluminum thickness is varied from 2 to 30 nm for two fixed thickness of the base electrode: 50 and 200 nm. The appropriate conditions for a full suppression of the so called "knee" structure at the gap voltage in the current-voltage characteristic are experimentally determined and theoretically interpreted in the framework of the microscopic theory. The influence of the additional aluminum layer in a composite base electrode on the properties of the tunnel junction have been studied in dependence on the aluminum thickness and distance of this layer from the barrier. The obtained results demonstrate that the current-voltage characteristics of tunnel junction can be engineering by an appropriate layer thickness of compound base electrode.
Development of autonomous and self-driving vehicles requires agile and reliable services to manage hazardous road situations. Vehicular Network is the medium that can provide high-quality services for self-driving vehicles. The majority of service requests in Vehicular Networks are delay intolerant (e.g., hazard alerts, lane change warning) and require immediate service. Therefore, Vehicular Networks, and particularly, Vehicleto-Infrastructure (V2I) systems must provide a consistent realtime response to autonomous vehicles. During peak hours or disasters, when a surge of requests arrives at a Base Station, it is challenging for the V2I system to maintain its performance, which can lead to hazardous consequences. Hence, the goal of this research is to develop a V2I system that is robust against uncertain request arrivals. To achieve this goal, we propose to dynamically allocate service requests among Base Stations. We develop an uncertainty-aware resource allocation method for the federated environment that assigns arriving requests to a Base Station so that the likelihood of completing it on-time is maximized. We evaluate the system under various workload conditions and oversubscription levels. Simulation results show that edge federation can improve robustness of the V2I system by reducing the overall service miss rate by up to 45%.
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